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README.md

+# Fundamentals of Machine Learning and Deep Learning
+
+Workshop at HFT Summer School 2025, Michael Mommert
+
+## Lectures
+
+We will have one lecture each on the basics of machine learning and deep learning. Lecture slides can be found in the `slides/` directory. For each lecture, there is a compressed slide deck without animations.
+
+## Exercises
+
+We will look at some Python example code for both machine learning and deep learning. You can access the Notebooks via *binder*. Launchers are available below:
+
+* [Regression Notebook](https://mybinder.org/v2/gh/Hochschule-fuer-Technik-Stuttgart/teaching-mommert/main?labpath=regression%2Fml%2Fcaliforniahousing%2Fregression_ml_californiahousing.ipynb)
+* [Classification Notebook](https://mybinder.org/v2/gh/Hochschule-fuer-Technik-Stuttgart/teaching-mommert/main?labpath=classification%2Fpixel-wise%2Fml%2Fsentinel-2%2Fclassification_pixel-wise_ml_sentinel-2.ipynb)
+* [Neural Network Notebook](https://mybinder.org/v2/gh/Hochschule-fuer-Technik-Stuttgart/teaching-mommert/main?labpath=classification%2Fpixel-wise%2Fmlp%2Fsentinel-2%2Fclassification_pixel-wise_mlp_sentinel-2.ipynb)
+
+More example Notebooks are available [here](https://github.com/Hochschule-fuer-Technik-Stuttgart/teaching-mommert).
+
+## License
+
+All materials are provided under MIT licence.
+
+
+